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Published on 31 July 2024
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Xu,S. (2024). Decision tree C4.5 algorithm for generative AI technology ethics--Based on the results of the questionnaire. Applied and Computational Engineering,87,33-40.
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Decision tree C4.5 algorithm for generative AI technology ethics--Based on the results of the questionnaire

Sihan Xu *,1,
  • 1 North China University of Technology

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/87/20241543

Abstract

With the development of AI technology, generative AI has gradually entered the life of the public, for example, the explosion of CHAT-GPT has allowed more people to see the huge potential and obvious advantages of generative AI. However, in the process of generative AI operation, events that violate social responsibility and ethics often occur, which makes the research on the scientific and technological ethics of generative AI more urgent. In the past literature and research, many industry experts have analysed the impact of generative AI on specific industries, but everyone is or will be a user of generative AI, so we should pay attention to the study of the people's scientific and technological ethical issues of generative AI after putting aside the industry background, so this paper collects primary data by means of questionnaire surveys to find out the public's awareness of generative AI and their perception of generative AI. and attitudes towards generative AI, and using the decision tree C4.5 algorithm with Python as the tool, it is used to respond to people's awareness of generative AI and the public's perception of the relationship between the various factors of the ethical issues of

Keywords

Generative AI, Decision Tree Algorithms, Ethics of Technology

[1]. Huang, M.-H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155-172.

[2]. Aaker JL (1997) Dimensions of brand personality. J. Marketing Res. 34(3):347–356.

[3]. Nazarovets, S., & Teixeira da Silva, J. A. (2024). ChatGPT as an “author”: Bibliometric analysis to assess the validity of authorship. Accountability in Research, 1–11.

[4]. Stokel-Walker, C., & van Noorden, R. (2023). What ChatGPT and generative AI mean for science. Nature, 614, 214-216.

[5]. Rao, S.J., Isath, A., Krishnan, P. et al.(2024) ChatGPT: A Conceptual Review of Applications and Utility in the Field of Medicine. J Med Syst 48-59.

Cite this article

Xu,S. (2024). Decision tree C4.5 algorithm for generative AI technology ethics--Based on the results of the questionnaire. Applied and Computational Engineering,87,33-40.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 6th International Conference on Computing and Data Science

Conference website: https://www.confcds.org/
ISBN:978-1-83558-585-6(Print) / 978-1-83558-586-3(Online)
Conference date: 12 September 2024
Editor:Alan Wang, Roman Bauer
Series: Applied and Computational Engineering
Volume number: Vol.87
ISSN:2755-2721(Print) / 2755-273X(Online)

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